Adaptively Tracking Spectrum Features For Endpoint Detection

ABSTRACT

A method of controlling polishing includes polishing a substrate, monitoring a substrate during polishing with an in-situ monitoring system, generating a sequence of values from measurements from the in-situ monitoring system, fitting a non-linear function to the sequence of values, determining a projected time at which the non-linear function reaches a target value; and determining at least one of a polishing endpoint or an adjustment for a polishing rate based on the projected time.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No. 12/271,674, filed on Nov. 14, 2008, the disclosure of which is incorporated by reference.

TECHNICAL FIELD

The present disclosure relates to optical monitoring during chemical mechanical polishing of substrates.

BACKGROUND

An integrated circuit is typically formed on a substrate by the sequential deposition of conductive, semiconductive, or insulative layers on a silicon wafer. One fabrication step involves depositing a filler layer over a non-planar surface and planarizing the filler layer. For certain applications, the filler layer is planarized until the top surface of a patterned layer is exposed. A conductive filler layer, for example, can be deposited on a patterned insulative layer to fill the trenches or holes in the insulative layer. After planarization, the portions of the conductive layer remaining between the raised pattern of the insulative layer form vias, plugs, and lines that provide conductive paths between thin film circuits on the substrate. For other applications, such as oxide polishing, the filler layer is planarized until a predetermined thickness is left over the non planar surface. In addition, planarization of the substrate surface is usually required for photolithography.

Chemical mechanical polishing (CMP) is one accepted method of planarization. This planarization method typically requires that the substrate be mounted on a carrier or polishing head. The exposed surface of the substrate is typically placed against a rotating polishing pad. The carrier head provides a controllable load on the substrate to push it against the polishing pad. An abrasive polishing slurry is typically supplied to the surface of the polishing pad.

One problem in CMP is determining whether the polishing process is complete, i.e., whether a substrate layer has been planarized to a desired flatness or thickness, or when a desired amount of material has been removed. Variations in the slurry distribution, the polishing pad condition, the relative speed between the polishing pad and the substrate, and the load on the substrate can cause variations in the material removal rate. These variations, as well as variations in the initial thickness of the substrate layer, cause variations in the time needed to reach the polishing endpoint. Therefore, the polishing endpoint cannot be determined merely as a function of polishing time.

In some systems, a substrate is optically monitored in-situ during polishing, e.g., through a window in the polishing pad. However, existing optical monitoring techniques may not satisfy increasing demands of semiconductor device manufacturers.

SUMMARY

In some monitoring processes, a linear function is fit to a sequence of values generated by an in-situ monitoring system, e.g., during the polishing processes. For example, a sequence of spectra can be measured in-situ, and a characterizing value can be generated for each spectrum from the sequence. Unfortunately, if the polishing rate is changing gradually as polishing progresses, the linear function may not accurately predict the desired polishing endpoint. In addition, even if the polishing rate is stable, the sequence of values may not be linear. One approach is to fit a non-linear function to the sequence of values. Projection of the non-linear function to a target value can provide a more accurate calculation of the time at which the substrate will reach the desired polishing endpoint.

In one aspect, a method of controlling polishing includes polishing a substrate, monitoring a substrate during polishing with an in-situ monitoring system, generating a sequence of values from measurements from the in-situ monitoring system, fitting a non-linear function to the sequence of values, determining a projected time at which the non-linear function reaches a target value; and determining at least one of a polishing endpoint or an adjustment for a polishing rate based on the projected time.

Implementations can include on or more of the following features. The non-linear function may include a second order or higher polynomial function, e.g., the non-linear function may be a second order polynomial function. Fitting the non-linear function to the sequence of values may include a Savitzky-Golay method. The in-situ monitoring system may include a spectrographic monitoring system and a sequence of spectra of light from the substrate may be measured during polishing with the spectrographic monitoring system. For each measured spectrum from the sequence of spectra, a best matching reference spectrum may be found from a library having a plurality of reference spectra, and generating the sequence of values may include, for each best matching reference spectrum, determining a value associated the best matching reference spectrum. The sequence of values may be a sequence of thicknesses values. For each measured spectrum from the sequence of spectra, a position or width of a peak or valley of the measured spectrum may be found to generate a sequence of position or width values, and the sequence of values may be generated from the sequence of position or width values. The sequence of values may be a sequence of wavelength values of positions of the peak or valley Polishing the substrate may include polishing a dielectric and/or semiconductor layer. The in-situ monitoring system may include an eddy current monitoring system, and the sequence of values may be generated with the eddy current monitoring system. Polishing the substrate may include polishing a metal layer. The polishing may be halted when the non-linear function matches or exceeds a target value. The substrate may include a plurality of zones, and a polishing rate of each zone may be independently controllable by an independently variable polishing parameter. For each zone, a sequence of values from measurements may be generated from the in-situ monitoring system during polishing. A sequence of spectra may be measured from each zone during polishing. For each zone, a sequence of values may be generated, including for each measured spectrum of the sequence of spectra, determining a wavelength or width of a peak or valley of a spectral feature. Based on the sequence of values for each zone, the polishing parameter for at least one zone may be adjusted to adjust the polishing rate of the at least one zone such that the plurality of zones have a smaller difference in thickness at the polishing endpoint than without such adjustment.

Polishing the substrate may include polishing a layer that includes polysilicon and/or a dielectric material, and monitoring the substrate comprises monitoring the layer. The layer may consist of substantially pure polysilicon. The layer may consists of dielectric material. The layer may be a combination of polysilicon and dielectric material.

In another aspect, a method of controlling polishing includes polishing a substrate, measuring a sequence of spectra of light from the substrate during polishing, generating a sequence of values, including for each measured spectrum of the sequence of spectra, determining a wavelength or width of a peak or valley of a spectra feature, fitting a non-linear function to the sequence of values, determining a projected time at which the non-linear function reaches a target value, and determining at least one of a polishing endpoint or an adjustment for a polishing rate based on the projected time.

In another aspect, a non-transitory computer program product, tangibly embodied in a machine readable storage device, includes instructions to carry out the method.

Implementations may optionally include one or more of the following advantages. The time at which the substrate will reach the desired polishing endpoint can be calculated more accurately. Reliability of the endpoint system to detect a desired polishing endpoint can be improved, and within-wafer and wafer-to-wafer thickness non-uniformity (WIWNU and WTWNU) can be reduced.

The details of one or more implementations are set forth in the accompanying drawings and the description below. Other aspects, features, and advantages will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a chemical mechanical polishing apparatus.

FIG. 2 is an overhead view of a polishing pad and shows locations where in-situ measurements are taken.

FIG. 3A shows a spectrum obtained from in-situ measurements.

FIG. 3B illustrates the evolution of spectra obtained from in-situ measurements as polishing progresses.

FIG. 4A shows an example graph of a spectrum of light reflected from a substrate.

FIG. 4B shows the graph of FIG. 4A passed through a high pass filter.

FIG. 5A shows a spectrum of light reflected from a substrate.

FIG. 5B shows a contour plot of spectra obtained from in-situ measurements of light reflected from a substrate.

FIG. 6A shows an example graph of polishing progress, measured in characteristic difference versus time.

FIG. 6B shows an example graph of polishing progress, measured in characteristic difference versus time in which characteristics of two different features are measured in order to adjust the polishing rate of a substrate.

FIG. 7A shows another spectrum of light obtained from in-situ measurements.

FIG. 7B shows a spectrum of light obtained after the spectrum of FIG. 7A.

FIG. 7C shows another spectrum of light obtained after the spectrum of FIG. 7A.

FIG. 8 shows a method for selecting a peak to monitor.

FIG. 9 shows a method for obtaining target parameters for the selected peak.

FIG. 10 shows a method for endpoint determination.

FIG. 11 shows a method of setting for endpoint detection.

FIG. 12 shows another method for endpoint determination.

FIG. 13 illustrates a graph of total reflected intensity as a function of time during polishing.

FIG. 14 illustrates a graph of the wavelength position of a spectral peak as a function of time during polishing.

Like reference numbers and designations in the various drawings indicate like elements.

DETAILED DESCRIPTION

A variety of in-situ monitoring techniques can generate a sequence of values that depend on the thickness of a layer on the substrate. For example, one optical monitoring technique is to measure spectra of light reflected from a substrate during polishing, and identify a matching reference spectra from a library. Thickness values associated with the reference spectra provide a sequence of values. Another optical monitoring technique is to measure spectra of light reflected off of substrates during polishing and track a characteristic of a spectral feature, e.g., a wavelength or width of a peak or valley. The wavelength or width values from the measured spectra provide a sequence of values. As another example, an eddy current monitoring system can generate a sequence of values.

As noted above, if the polishing rate is changing gradually as polishing progresses, a linear function may not accurately predict the desired polishing endpoint. In addition, even if the polishing rate is stable, the sequence of values may not be linear. Instead, a non-linear function, e.g., a second-order polynomial, is fit to the sequence of values. Endpoint can be called at the projected time that the non-linear function reaches a target value or has changed by a target amount.

The substrate can be as simple as a single dielectric layer disposed on a semiconductor layer, or have a significantly more complex layer stack. For example, the substrate can include a first layer and a second layer disposed over the second layer. The first layer can be a dielectric, e.g., an oxide, such as silicon dioxide, or a low-k material, such as carbon doped silicon dioxide, e.g., Black Diamond™ (from Applied Materials, Inc.) or Coral™ (from Novellus Systems, Inc.). The second layer can be a barrier layer of different composition than the first layer. For example, the barrier layer can be a metal or a metal nitride, e.g., tantalum nitride or titanium nitride. Optionally disposed between the first and second layers are one or more additional layers, e.g., a low-k capping material, e.g., a material formed from tetraethyl orthosilicate (TEOS). Both the first layer and the second layer are at least semi-transparent. Together, the first layer and one or more additional layers (if present) provide a layer stack below the second layer. However, in some implementations, only a single layer, e.g., containing polysilicon and/or dielectric, e.g., a low-k, ultra low-k (ULK) or extremely low-k (ULK) material, is polished (although there may be additional layers below the layer being polished).

Chemical mechanical polishing can be used to planarize the substrate until the second layer is exposed. For example, if an opaque conductive material is present, it can be polished until the second layer, e.g., the barrier layer, is exposed. Then, the portion of the second layer remaining over the first layer is removed and the substrate is polished until the first layer, e.g., a dielectric layer, is exposed. In addition, it is sometimes desired to polish the first layer, e.g., the dielectric layer, until a target thickness remains or a target amount of material has been removed.

One method of polishing is to polishing the conductive layer on a first polishing pad at least until the second layer, e.g., the barrier layer, is exposed. In addition, a portion of the thickness of the second layer can be removed, e.g., during an overpolishing step at the first polishing pad. The substrate is then transferred to a second polishing pad, where the second layer, e.g., the barrier layer is completely removed, and a portion of the thickness of the underlying first layer, e.g., the low-k dielectric, is also removed. In addition, if present, the additional layer or layers between the first and second layer can be removed in the same polishing operation at the second polishing pad.

However, the initial thickness of the second layer may not be known when the substrate is transferred to the second polishing pad. As noted above, this can pose a problem for optical endpoint detection techniques that track a selected spectral feature characteristics in spectra measurements in order to determine endpoint at a target thickness.

However, this problem can be reduced if spectral feature tracking is triggered by another monitoring technique that can reliably detect removal of the second layer and exposure of the underlying first layer or layer structure. In addition, by measuring the initial thickness of the first layer and by calculating a target feature value from the initial thickness and the target thickness for the first layer, substrate-to-substrate uniformity of the thickness of the first layer can be improved.

Spectral features can include spectral peaks, spectral valleys, spectral inflection points, or spectral zero-crossings. Characteristics of the features can include a wavelength, a width, or an intensity.

FIG. 1 shows a polishing apparatus 20 operable to polish a substrate 10. The polishing apparatus 20 includes a rotatable disk-shaped platen 24, on which a polishing pad 30 is situated. The platen is operable to rotate about axis 25. For example, a motor can turn a drive shaft 22 to rotate the platen 24. The polishing pad 30 can be detachably secured to the platen 24, for example, by a layer of adhesive. When worn, the polishing pad 30 can be detached and replaced. The polishing pad 30 can be a two-layer polishing pad with an outer polishing layer 32 and a softer backing layer 34.

Optical access 36 through the polishing pad is provided by including an aperture (i.e., a hole that runs through the pad) or a solid window. The solid window can be secured to the polishing pad, although in some implementations the solid window can be supported on the platen 24 and project into an aperture in the polishing pad. The polishing pad 30 is usually placed on the platen 24 so that the aperture or window overlies an optical head 53 situated in a recess 26 of the platen 24. The optical head 53 consequently has optical access through the aperture or window to a substrate being polished.

The window can be, for example, a rigid crystalline or glassy material, e.g., quartz or glass, or a softer plastic material, e.g., silicone, polyurethane or a halogenated polymer (e.g., a fluoropolymer), or a combination of the materials mentioned. The window can be transparent to white light. If a top surface of the solid window is a rigid crystalline or glassy material, then the top surface should be sufficiently recessed from the polishing surface to prevent scratching. If the top surface is near and may come into contact with the polishing surface, then the top surface of the window should be a softer plastic material. In some implementations the solid window is secured in the polishing pad and is a polyurethane window, or a window having a combination of quartz and polyurethane. The window can have high transmittance, for example, approximately 80% transmittance, for monochromatic light of a particular color, for example, blue light or red light. The window can be sealed to the polishing pad 30 so that liquid does not leak through an interface of the window and the polishing pad 30.

In one implementation, the window includes a rigid crystalline or glassy material covered with an outer layer of a softer plastic material. The top surface of the softer material can be coplanar with the polishing surface. The bottom surface of the rigid material can be coplanar with or recessed relative to the bottom surface of the polishing pad. In particular, if the polishing pad includes two layers, the solid window can be integrated into the polishing layer, and the bottom layer can have an aperture aligned with the solid window.

A bottom surface of the window can optionally include one or more recesses. A recess can be shaped to accommodate, for example, an end of an optical fiber cable or an end of an eddy current sensor. The recess allows the end of the optical fiber cable or the end of the eddy current sensor to be situated at a distance, from a substrate surface being polished, that is less than a thickness of the window. With an implementation in which the window includes a rigid crystalline portion or glass like portion and the recess is formed in such a portion by machining, the recess is polished so as to remove scratches caused by the machining Alternatively, a solvent and/or a liquid polymer can be applied to the surfaces of the recess to remove scratches caused by machining The removal of scratches usually caused by machining reduces scattering and can improve the transmittance of light through the window.

The polishing pad's backing layer 34 can be attached to its outer polishing layer 32, for example, by adhesive. The aperture that provides optical access 36 can be formed in the pad 30, e.g., by cutting or by molding the pad 30 to include the aperture, and the window can be inserted into the aperture and secured to the pad 30, e.g., by an adhesive. Alternatively, a liquid precursor of the window can be dispensed into the aperture in the pad 30 and cured to form the window. Alternatively, a solid transparent element, e.g., the above described crystalline or glass like portion, can be positioned in liquid pad material, and the liquid pad material can be cured to form the pad 30 around the transparent element. In either of the later two cases, a block of pad material can be formed, and a layer of polishing pad with the molded window can be scythed from the block.

The polishing apparatus 20 includes a combined slurry/rinse arm 39. During polishing, the arm 39 is operable to dispense slurry 38 containing a liquid and a pH adjuster. Alternatively, the polishing apparatus includes a slurry port operable to dispense slurry onto polishing pad 30.

The polishing apparatus 20 includes a carrier head 70 operable to hold the substrate 10 against the polishing pad 30. The carrier head 70 is suspended from a support structure 72, for example, a carousel, and is connected by a carrier drive shaft 74 to a carrier head rotation motor 76 so that the carrier head can rotate about an axis 71. In addition, the carrier head 70 can oscillate laterally in a radial slot formed in the support structure 72. In operation, the platen is rotated about its central axis 25, and the carrier head is rotated about its central axis 71 and translated laterally across the top surface of the polishing pad.

The polishing apparatus also includes an optical monitoring system, which can be used to determine a polishing endpoint as discussed below. The optical monitoring system includes a light source 51 and a light detector 52. Light passes from the light source 51, through the optical access 36 in the polishing pad 30, impinges and is reflected from the substrate 10 back through the optical access 36, and travels to the light detector 52.

A bifurcated optical cable 54 can be used to transmit the light from the light source 51 to the optical access 36 and back from the optical access 36 to the light detector 52. The bifurcated optical cable 54 can include a “trunk” 55 and two “branches” 56 and 58.

As mentioned above, the platen 24 includes the recess 26, in which the optical head 53 is situated. The optical head 53 holds one end of the trunk 55 of the bifurcated fiber cable 54, which is configured to convey light to and from a substrate surface being polished. The optical head 53 can include one or more lenses or a window overlying the end of the bifurcated fiber cable 54. Alternatively, the optical head 53 can merely hold the end of the trunk 55 adjacent to the solid window in the polishing pad. The optical head 53 can be removed from the recess 26 as required, for example, to effect preventive or corrective maintenance.

The platen includes a removable in-situ monitoring module 50. The in-situ monitoring module 50 can include one or more of the following: the light source 51, the light detector 52, and circuitry for sending and receiving signals to and from the light source 51 and light detector 52. For example, the output of the detector 52 can be a digital electronic signal that passes through a rotary coupler, e.g., a slip ring, in the drive shaft 22 to the controller for the optical monitoring system. Similarly, the light source can be turned on or off in response to control commands in digital electronic signals that pass from the controller through the rotary coupler to the module 50.

The in-situ monitoring module 50 can also hold the respective ends of the branch portions 56 and 58 of the bifurcated optical fiber 54. The light source is operable to transmit light, which is conveyed through the branch 56 and out the end of the trunk 55 located in the optical head 53, and which impinges on a substrate being polished. Light reflected from the substrate is received at the end of the trunk 55 located in the optical head 53 and conveyed through the branch 58 to the light detector 52.

In one implementation, the bifurcated fiber cable 54 is a bundle of optical fibers. The bundle includes a first group of optical fibers and a second group of optical fibers. An optical fiber in the first group is connected to convey light from the light source 51 to a substrate surface being polished. An optical fiber in the second group is connected to receive light reflecting from the substrate surface being polished and convey the received light to the light detector 52. The optical fibers can be arranged so that the optical fibers in the second group form an X-like shape that is centered on the longitudinal axis of the bifurcated optical fiber 54 (as viewed in a cross section of the bifurcated fiber cable 54). Alternatively, other arrangements can be implemented. For example, the optical fibers in the second group can form V-like shapes that are mirror images of each other. A suitable bifurcated optical fiber is available from Verity Instruments, Inc. of Carrollton, Tex.

There is usually an optimal distance between the polishing pad window and the end of the trunk 55 of bifurcated fiber cable 54 proximate to the polishing pad window. The distance can be empirically determined and is affected by, for example, the reflectivity of the window, the shape of the light beam emitted from the bifurcated fiber cable, and the distance to the substrate being monitored. In one implementation, the bifurcated fiber cable is situated so that the end proximate to the window is as close as possible to the bottom of the window without actually touching the window. With this implementation, the polishing apparatus 20 can include a mechanism, e.g., as part of the optical head 53, that is operable to adjust the distance between the end of the bifurcated fiber cable 54 and the bottom surface of the polishing pad window. Alternatively, the proximate end of the bifurcated fiber cable 54 is embedded in the window.

The light source 51 is operable to emit white light. In one implementation, the white light emitted includes light having wavelengths of 200-800 nanometers. A suitable light source is a xenon lamp or a xenon-mercury lamp.

The light detector 52 can be a spectrometer. A spectrometer is basically an optical instrument for measuring properties of light, for example, intensity, over a portion of the electromagnetic spectrum. A suitable spectrometer is a grating spectrometer. Typical output for a spectrometer is the intensity of the light as a function of wavelength.

The light source 51 and light detector 52 are connected to a computing device operable to control their operation and to receive their signals. The computing device can include a microprocessor situated near the polishing apparatus, e.g., a personal computer. With respect to control, the computing device can, for example, synchronize activation of the light source 51 with the rotation of the platen 24. As shown in FIG. 2, the computer can cause the light source 51 to emit a series of flashes starting just before and ending just after the substrate 10 passes over the in-situ monitoring module 50. Each of points 201-211 represents a location where light from the in-situ monitoring module 50 impinged upon and reflected off of the substrate 10. Alternatively, the computer can cause the light source 51 to emit light continuously starting just before and ending just after the substrate 10 passes over the in-situ monitoring module 50.

The spectra obtained as polishing progresses, e.g., from successive sweeps of the sensor in the platen across the substrate, provide a sequence of spectra. In some implementations, the light source 51 emits a series of flashes of light onto multiple portions of the substrate 10. For example, the light source can emit flashes of light onto a center portion of the substrate 10 and an exterior portion of the substrate 10. Light reflected off of the substrate 10 can be received by the light detector 52 in order to determine multiple sequences of spectra from multiple portions of the substrate 10. Features can be identified in the spectra where each feature is associated with one portion of the substrate 10. The features can be used, for example, in determining an endpoint condition for polishing of the substrate 10. In some implementations, monitoring of multiple portions of the substrate 10 allows for changing the polishing rate on one or more of the portions of the substrate 10.

With respect to receiving signals, the computing device can receive, for example, a signal that carries information describing a spectrum of the light received by the light detector 52. FIG. 3A shows examples of a spectrum measured from light that is emitted from a single flash of the light source and that is reflected from the substrate. Spectrum 302 is measured from light reflected from a product substrate. Spectrum 304 is measured from light reflected from a base silicon substrate (which is a wafer that has only a silicon layer). Spectrum 306 is from light received by the optical head 53 when there is no substrate situated over the optical head 53. Under this condition, referred to in the present specification as a dark condition, the received light is typically ambient light.

The computing device can process the above-described signal, or a portion thereof, to determine an endpoint of a polishing step. Without being limited to any particular theory, the spectrum of light reflected from the substrate 10 evolves as polishing progresses. FIG. 3B provides an example of the evolution of the spectrum as polishing of a film of interest progresses. The different lines of spectrum represent different times in the polishing. As can be seen, properties of the spectrum of the reflected light change as a thickness of the film changes, and particular spectrums are exhibited by particular thicknesses of the film. When a peak (that is, a local maximum) in the spectrum of reflected light is observed as the polishing of a film progresses, the height of the peak typically changes, and the peak tends to grow wider as material is removed. In addition to widening, the wavelength at which a particular peak is located typically increases as polishing progresses. In some implementations, the wavelength at which a particular peak is located typically decreases as polishing progresses. For example, peak 310(1) illustrates a peak in the spectrum at a certain time during polishing, and peak 310(2) illustrates the same peak at a later time during polishing. Peak 310(2) is located at a longer wavelength and is wider than peak 310(1).

The relative change in the wavelength and/or width of a peak (e.g., the width measured at a fixed distance below the peak or measured at a height halfway between the peak and the nearest valley), the absolute wavelength and/or width of the peak, or both can be used to determine the endpoint for polishing according to an empirical formula. The best peak (or peaks) to use when determining the endpoint varies depending on what materials are being polished and the pattern of those materials.

In some implementations, a change in peak wavelength can be used to determine endpoint. For example, when the difference between the starting wavelength of a peak and the current wavelength of the peak reaches a target difference, the polishing apparatus 20 can stop polishing the substrate 10. Alternatively, features other than peaks can be used to determine a difference in the wavelength of light reflected from the substrate 10. For example, the wavelength of a valley, an inflection point, or an x- or y-axis intercept can be monitored by the light detector 52, and when the wavelength has changed by a predetermined amount, the polishing apparatus 20 can stop polishing the substrate 10.

In some implementations, the characteristic that is monitored is the width or the intensity of the feature instead of, or in addition to the wavelength. Features can shift on the order of 40 nm to 120 nm, although other shifts are possible, For example, the upper limit could be much greater, especially in the case of a dielectric polish.

FIG. 4A provides an example of a measured spectrum 400 a of light reflected from the substrate 10. The optical monitoring system can pass the spectrum 400 a through a high-pass filter in order to reduce the overall slope of the spectrum, resulting in a spectrum 400 b shown in FIG. 4B. During processing of multiple substrates in a batch, for example, large spectra differences can exist among wafers. A high-pass filter can be used to normalize the spectra in order to reduce spectra variations across substrates in the same batch. An exemplary high-pass filter can have a cutoff of 0.005 Hz and a filter order of 4. The high-pass filter is not only used to help filter out sensitivity to underlying variation, but also to “flatten” out the legitimate signal to make feature tracking easier.

In order for a user to select which feature of the endpoint to track to determine the endpoint, a contour plot can be generated and displayed to the user. FIG. 5B provides an example of a contour plot 500 b generated from multiple spectra measurements of light reflected off of the substrate 10 during polishing, and FIG. 5A provides an example of a measured spectrum 500 a from a particular moment in the contour plot 500 b. The contour plot 500 b includes features, such as a peak area 502 and a valley area 504 which result from associated peaks 502 and valleys 504 on the spectrum 500 a. As time progresses, the substrate 10 is polished and the light reflected from the substrate changes, as shown by changes to the spectral features in the contour plot 500 b.

In order to generate the contour plot 500 b, a test substrate can be polished, and the light reflected from the test substrate can be measured by the light detector 52 during polishing to generate a sequence of spectra of light reflected from the substrate 10. The sequence of spectra can be stored, e.g., in a computer system, which optionally can be part of the optical monitoring system. Polishing of the set up substrate can start at time T1 and continue past an estimated endpoint time.

When polishing of the test substrate is complete, the computer renders the contour plot 500 b for presentation to an operator of the polishing apparatus 20, e.g., on a computer monitor. In some implementations, the computer color-codes the contour-plot, e.g., by assigning red to the higher intensity values in the spectra, blue to the lower intensity values in the spectra, and intermediate colors (orange through green) to the intermediate intensity values in the spectra. In other implementations, the computer creates a grayscale contour plot by assigning the darkest shade of gray to lower intensity values in the spectra, and the lightest shade of gray to higher intensity values in the spectra, with intermediate shades for the intermediate intensity values in the spectra. Alternatively, the computer can generate a 3-D contour plot with the largest z value for higher intensity values in the spectra, and the smallest z value for lower intensity values in the spectra, with intermediate z values for the intermediate values in the spectra. A 3-D contour plot can be, for example, displayed in color, grayscale, or black and white. In some implementations, the operator of the polishing apparatus 20 can interact with a 3-D contour plot in order to view different features of the spectra.

The contour plot 500 b of the reflected light generated from monitoring of the test substrate during polishing can contain, for example, spectral features such as peaks, valleys, spectral zero-crossing points, and inflection points. The features can have characteristics such as wavelengths, widths, and/or intensities. As shown by the contour plot 500 b, as the polishing pad 30 removes material from the top surface of the set up substrate, the light reflected off of the set up substrate can change over time, so feature characteristics change over time.

Prior to polishing of the device substrates, an operator of the polishing apparatus 20 can view the contour plot 500 b and select a feature characteristic to track during processing of a batch of substrates that have similar die features as the set up substrate. For example, the wavelength of a peak 506 can be selected for tracking by the operator of the polishing apparatus 20. A potential advantage of the contour plot 500 b, particularly a color-coded or 3-D contour plot, is that such a graphical display makes the selection of a pertinent feature by the user easier, since the features, e.g., features with characteristics that change linearly or parabolically with time, are easily visually distinguishable.

In order to select an endpoint criterion, the characteristic of the selected feature can be calculated by linear interpolation based on the pre-polish thickness and the post-polish thickness of the test substrate. For example, thicknesses D1 and D2 of the layer on the test substrate can be measured at pre-polish (e.g., the thickness of the test substrate before time T1 when polishing starts) and at post-polish (e.g., the thickness of the test substrate after time T2 when polishing ends) respectively, and the values of the characteristic can be measured at the time T′ at which the target thickness D′ is achieved. T′ can be calculated from T′=T1+(T2−T1)*(D2−D′)/(D2−D1), and the value V′ of the characteristic can be determined from the spectrum measured at time T′. Alternatively, the value of T′ could be calculated from a non-linear function, e.g., a second order polynomial, that is fit to measured data from in-situ monitoring of the test substrate.

A target difference, W, for the characteristic of the selected feature, such as a specific change in the wavelength of the peak 506, can be determined from V′-V1, where V1 is the initial characteristic value (at the time T1). Thus, the target difference δV can be the change from the initial value of the characteristic V1 before polishing at time T1 to the value of the characteristic V′ at time T′ when polishing is expected to be completed. An operator of the polishing apparatus 20 can enter a target difference 604 (e.g., δV) for the feature characteristic to change into a computer associated with the polishing apparatus 20.

In order to determine the value of V′ which in turn determines the value of points 602, a robust line fitting can be used to fit a line 508 to the measured data. The value of line 508 at time T′ minus the value of line 508 at T1 can be used to determine points 602. Alternatively, in order to determine the value of V′ which in turn determines the value of points 602, a non-linear function, e.g., a second order polynomial, can be fit to the measured data. The value of the non-linear function at time T′ minus the value of the non-linear function 508 at T1 can be used to determine points 602.

The feature, such as the spectral peak 506, can be selected based on correlation between the target difference of the feature characteristic and the amount of material removed from the set up substrate during polishing. The operator of the polishing apparatus 20 can select a different feature and/or feature characteristic in order to find a feature characteristic with a good correlation between the target difference of the characteristic and the amount of material removed from the set up substrate.

In other implementations, endpoint determination logic determines the spectral feature to track and the endpoint criterion.

Turning now to the polishing of a device substrate, FIG. 6A is an example graph 600 a of difference values 602 a-d of a tracked feature characteristic during polishing of a device substrate 10. The substrate 10 can be part of a batch of substrates being polished where an operator of the polishing apparatus 20 selected a feature characteristic, such as the wavelength of a peak or a valley, to track from the contour plot 500 b of a set up substrate.

As the substrate 10 is polished, the light detector 52 measures spectra of light reflected from the substrate 10. The endpoint determination logic uses the spectra of light to determine a sequence of values for the feature characteristic. The values of the selected feature characteristic can change as material is removed from the surface of the substrate 10. The difference between the sequence of values of the feature characteristic and the initial value of the feature characteristic V1 is used to determine the difference values 602 a-d.

As the substrate 10 is polished the endpoint determination logic can determine the current value of the feature characteristic being tracked. In some implementations, when the current value of the feature has changed from the initial value by the target difference 604, endpoint can be called.

A non-linear function 606, e.g., a polynomial function of second order, e.g., a second-order polynomial function (e.g., a parabolic curve) is fit to the sequence of values. The second-order polynomial function F can be expressed as

F=A*x ²+B*x+C

where A, B and C are coefficients of the, and x represents time or number of platen rotations.

The non-linear function should be monotonic over any expected polishing time. Fitting of the non-linear function to the sequence of values can be performed by applying a Savitzky-Golay filter. A possible advantage of the Savitzky-Golay filter is that it is more stable than some other fitting algorithms.

The polishing endpoint time can be predicted based on the non-linear function 606. In addition, polishing can be halted at an endpoint time TE where the non-linear function 214 crosses a target value IT.

The coefficients of the non-linear function 606, can change during polishing of the substrate 10 as new difference values are calculated. In some implementations, the time at which the non-linear function 606 reaches the target difference 604 provides an estimated endpoint time 608. As the function of the non-linear function 606 changes to accommodate new difference values, the estimated endpoint time 608 can change.

In some implementations, the function of the non-linear function 606 is used to determine the amount of material removed from the substrate 10 and a change in the current value determined by the function is used to determine when the target difference has been reached and endpoint needs to be called. The non-linear function 606 tracks amount of material removed. Alternatively, when removing a specific thickness of material from the substrate 10, a change in the current value determined by the function can be used to determine the amount of material removed from the top surface of the substrate 10 and when to call endpoint. For example, an operator can set the target difference to be a change in wavelength of the selected feature by 50 nanometers. For example, the change in the wavelength of a selected peak can be used to determine how much material has been removed from the top layer of the substrate 10 and when to call endpoint.

At time T1, before polishing of the substrate 10, the characteristic value difference of the selected feature is 0. As the polishing pad 30 begins to polish the substrate 10 the characteristic values of the identified feature can change as material is polished off of the top surface of the substrate 10. For example, during polishing the wavelength of the selected feature characteristic can move to a higher or lower wavelength. Excluding noise effects, the wavelength, and thus the difference in wavelength, of the feature tends to change monotonically, and often linearly. At time T′ endpoint determination logic determines that the identified feature characteristic has changed by the target difference, δV, and endpoint can be called. For example, when the wavelength of the feature has changed by a target difference of 50 nanometers, endpoint is called and the polishing pad 30 stops polishing the substrate 10.

When processing a batch of substrates the optical monitoring system 50 can, for example, track the same spectral feature across all of the substrates. The spectral feature can be associated with the same die feature on the substrates. The starting wavelength of the spectral feature can change from substrate to substrate across the batch based on underlying variations of the substrates. In some implementations, in order to minimize variability across multiple substrates, endpoint determination logic can call endpoint when the selected feature characteristic value or a function fit to values of the feature characteristic changes by an endpoint metric, EM, instead of the target difference. The endpoint determination logic can use an expected initial value, EIV, determined from a set up substrate. At time T1 when the feature characteristic being tracked on the substrate 10 is identified, the endpoint determination logic determines the actual initial value, AIV, for a substrate being processed. The endpoint determination logic can use an initial value weight, IVW, to reduce the influence of the actual initial value on the endpoint determination while taking into consideration variations in substrates across a batch. Substrate variation can include, for example, substrate thickness or the thickness of underlying structures. The initial value weight can correlate to the substrate variations in order to increase uniformity between substrate to substrate processing. The endpoint metric can be, for example, determined by multiplying the initial value weight by the difference between the actual initial value and the expected initial value and adding the target difference, e.g., EM=IVW*(AIV−EIV)+δV.

In some implementations, a weighted combination is used to determine endpoint. For example, the endpoint determination logic can calculate an initial value of the characteristic from the function and a current value of the characteristic from the function, and a first difference between the initial value and the current value. The endpoint determination logic can calculate a second difference between the initial value and a target value and generate a weighted combination of the first difference and the second difference.

FIG. 6B is an example graph 600 b of characteristic measurement differences versus time taken at two portions of the substrate 10. For example, the optical monitoring system 50 can track one feature located toward an edge portion of the substrate 10 and another feature located toward a center portion of the substrate 10 in order to determine how much material has been removed from the substrate 10. When testing a set up substrate, an operator of the polishing apparatus 20 can, for example, identify two features to track that correspond to different portions of the set up substrate. In some implementations, the spectral features correspond with the same type of die features on the set up substrate. In other implementations, the spectral features are associated with different types of die features on the set up substrate. As the substrate 10 is being polished, the light detector 52 can measure a sequence of spectra of reflected light from the two portions of the substrate 10 that correspond with the selected features of the set up substrate. A sequence of values associated with characteristics of the two features can be determined by endpoint determination logic.

A sequence of first difference values 610 a-b can be calculated for a feature characteristic in a first portion of the substrate 10 by subtracting the initial characteristic value from the current characteristic value as polishing time progresses. A sequence of second difference values 612 a-b can similarly be calculated for a feature characteristic in a second portion of the substrate 10.

A first non-linear funct 614 can be fit to the first difference values 610 a-b and a second non-linear function 616 can be fit to the second difference values 612 a-b. The first non-linear function 614 and the second non-linear function 616 can be determined be polynomial functions of the same order, and the projection of the first and second non-linear functions can determine an estimated polishing endpoint time 618 or an adjustment to the polishing rate 620 of the substrate 10.

During polishing, an endpoint calculation based on a target difference 622 is made at time TC with the first function for the first portion of the substrate 10 and with the second function for the second portion of the substrate. If the estimated endpoint time for the first portion of the substrate and the second portion of the substrate differ (e.g., the first portion will reach the target thickness before the second portion) an adjustment to the polishing rate 620 can be made so that the first function and the second function will have the same endpoint time 618. In some implementations, the polishing rates of both the first portion and the second portion of the substrate are adjusted so that endpoint is reached at both portions simultaneously. Alternatively, the polishing rate of either the first portion or the second portion can be adjusted.

The polishing rates can be adjusted by, for example, increasing or decreasing the pressure in a corresponding region of the carrier head 70. The change in polishing rate can be assumed to be directly proportional to the change in pressure, e.g., a simple Prestonian model. For example, when a the first region of the substrate 10 is projected to reach the target thickness at a time TA, and the system has established a target time TT, the carrier head pressure in the corresponding region before time T3 can be multiplied by TT/TA to provide the carrier head pressure after time T3. Additionally, a control model for polishing the substrates can be developed that takes into account the influences of platen or head rotational speed, second order effects of different head pressure combinations, the polishing temperature, slurry flow, or other parameters that affect the polishing rate. At a subsequent time during the polishing process, the rates can again be adjusted, if appropriate.

In some implementations, a computing device uses a wavelength range in order to easily identify a selected spectral feature in a measured spectrum of light reflected from the device substrate 10. The computing device searches the wavelength range for the selected spectral feature in order to distinguish the selected spectral feature from other spectral features that are similar to the selected spectral feature in the measured spectrum, e.g., in intensity, width, or wavelength.

FIG. 7A shows an example of a spectrum 700 a measured from light received by the light detector 52. The spectrum 700 a includes a selected spectral feature 702, e.g., a spectral peak. The selected spectral feature 702 can be selected by endpoint determination logic for tracking during CMP of the substrate 10. A characteristic 704 (e.g., the wavelength) of the selected spectral feature 702 can be identified by the endpoint determination logic. When the characteristic 704 has changed by a target difference, the endpoint determination logic calls endpoint.

In some implementations, the endpoint determination logic determines a wavelength range 706 over which to search for the selected spectral feature 702. The wavelength range 706 can have a width of between about 50 and about 200 nanometers. In some implementations, the wavelength range 706 is predetermined, e.g., specified by an operator, e.g., by receiving user input selecting the wavelength range, or specified as a process parameter for a batch of substrates, by retrieving the wavelength range from a memory associating the wavelength range with the batch of substrates. In some implementations, the wavelength range 706 is based on historical data, e.g., the average or maximum distance between consecutive spectrum measurements. In some implementations, the wavelength range 706 is based on information about a test substrate, e.g., twice the target difference δV.

FIG. 7B is an example of a spectrum 700 b measured from light received by the light detector 52. For example, the spectrum 700 b is measured during the rotation of the platen 24 directly after the spectrum 700 a was taken. In some implementations, the endpoint determination logic determines the value of the characteristic 704 in the previous spectrum 700 a (e.g., 520 nm) and adjusts the wavelength range 706 so that the center of a wavelength range 708 is positioned closer to the characteristic 704.

In some implementations, the endpoint determination logic uses the non-linear function 606 to determine an expected current value of the characteristic 704. For example, the endpoint determination logic can use the current polishing time to determine the expected difference and determine the expected current value of the characteristic 704 by adding the expected difference to the initial value V1 of the characteristic 704. The endpoint determination logic can center the wavelength range 708 on the expected current value of the characteristic 704.

FIG. 7C is another example of a spectrum 700 c measured from light received by the light detector 52. For example, the spectrum 700 c is measured during the rotation of the platen 24 directly after the spectrum 700 a was taken. In some implementations, the endpoint determination logic uses the previous value of the characteristic 704 for the center of a wavelength range 710.

For example, the endpoint determination logic determines the average variance between values of the characteristic 704 determined during two consecutive passes of the optical head 53 below the substrate 10. The endpoint determination logic can set the width of the wavelength range 710 to twice the average variance. In some implementations, the endpoint determination logic uses the standard deviation of the variance between values of the characteristic 704 in determining the width of the wavelength range 710.

In some implementations, the width of the wavelength range 706 is the same for all spectra measurements. For example, the width of the wavelength range 706, the wavelength range 708, and the wavelength range 710 are the same. In some implementations, the widths of the wavelength ranges are different. For example, when the characteristic 704 is estimated to change by 2 nanometers from the previous measurement of the characteristic, the width of the wavelength range 708 is 60 nanometers. When the characteristic 704 is estimated to change by 5 nanometers from the previous measurement of the characteristic, the width of the wavelength range 708 is 80 nanometers, a greater wavelength range than the range for a smaller change in the characteristic.

In some implementations, the wavelength range 706 is the same for all spectra measurements during polishing of the substrate 10. For example, the wavelength range 706 is 475 nanometers to 555 nanometers and the endpoint determination logic searches for the selected spectral feature 702 in the wavelengths between 475 nanometers and 555 nanometers for all spectra measurements taken during polishing of the substrate 10, although other wavelength ranges are possible. The wavelength range 706 can be selected by user input as a subset of the full spectral range measured by the in-situ monitoring system.

In some implementations, the endpoint determination logic searches for the selected spectral feature 702 in a modified wavelength range in some of the spectra measurements and in a wavelength range used for a previous spectrum in remainder of the spectra. For example, the endpoint determination logic searches for the selected spectral feature 702 in the wavelength range 706 for a spectrum measured during a first rotation of the platen 24 and the wavelength range 708 for a spectrum measured during a consecutive rotation of the platen 24, where both measurements were taken in a first area of the substrate 10. Continuing the example, the endpoint determination logic searches for another selected spectral feature in the wavelength range 710 for two spectra measured during the same platen rotations, where both measurements were taken in a second area of the substrate 10 that is different from the first area.

In some implementations, the selected spectral feature 702 is a spectral valley or a spectral zero-crossing point. In some implementations, the characteristic 704 is an intensity or a width of a peak or valley (e.g., the width measured at a fixed distance below the peak or measured at a height halfway between the peak and the nearest valley).

FIG. 8 shows a method 800 for selecting a target difference δV to use when determining the endpoint for the polishing process. Properties of a substrate with the same pattern as the product substrate are measured (step 802). The substrate which is measured is referred to in the instant specification as a “set-up” substrate. The set-up substrate can simply be a substrate which is similar to or the same as the product substrate, or the set-up substrate can be one substrate from a batch of product substrates. The properties that are measured can include a pre-polished thickness of a film of interest at a particular location of interest on the substrate. Typically, the thicknesses at multiple locations are measured. The locations are usually selected so that a same type of die feature is measured for each location. Measurement can be performed at a metrology station. The in-situ optical monitoring system can measure a spectrum of light reflected off of the substrate before polishing.

The set-up substrate is polished in accordance with a polishing step of interest and the spectra obtained during polishing are collected (step 804). Polishing and spectral collection can be performed at the above described-polishing apparatus. The spectra are collected by the in-situ monitoring system during polishing. The substrate is overpolished, i.e., polished past an estimated endpoint, so that the spectrum of the light that is reflected from the substrate when the target thickness is achieved can be obtained.

Properties of the overpolished substrate are measured (step 806). The properties include post-polished thicknesses of the film of interest at the particular location or locations used for the pre-polish measurement.

The measured thicknesses and the collected spectra are used to select, by examining the collected spectra, a particular feature, such as a peak or a valley, to monitor during polishing (step 808). The feature can be selected by an operator of the polishing apparatus or the selection of the feature can be automated (e.g., based on conventional peak-finding algorithms and an empirical peak-selection formula). For example, the operator of the polishing apparatus 20 can be presented with the contour plot 500 b and the operator can select a feature to track from the contour plot 500 b as described above with reference to FIG. 5B. If a particular region of the spectrum is expected to contain a feature that is desirable to monitor during polishing (e.g., due to past experience or calculations of feature behavior based on theory), only features in that region need be considered. A feature is typically selected that exhibits a correlation between the amount of material removed from the top of the set-up substrate as the substrate is polished.

Linear interpolation can be performed using the measured pre-polish film thickness and post-polish substrate thickness to determine an approximate time that the target film thickness was achieved. The approximate time can be compared to the spectra contour plot in order to determine the endpoint value of the selected feature characteristic. The difference between the endpoint value and the initial value of the feature characteristic can be used as a target difference. In some implementations, a function is fit to the values of the feature characteristic in order to normalize the values of the feature characteristic. The difference between the endpoint value of the function and the initial value of the function can be used as the target difference. The same feature is monitored during the polishing of the rest of the batch of substrates.

Optionally, the spectra are processed to enhance accuracy and/or precision. The spectra can be processed, for example: to normalize them to a common reference, to average them, and/or to filter noise from them. In one implementation, a low-pass filter is applied to the spectra to reduce or eliminate abrupt spikes.

The spectral feature to monitor typically is empirically selected for particular endpoint determination logic so that the target thickness is achieved when the computer device calls an endpoint by applying the particular feature-based endpoint logic. The endpoint determination logic uses the target difference in feature characteristic to determine when an endpoint should be called. The change in characteristic can be measured relative to the initial characteristic value of the feature when polishing begins. Alternatively, the endpoint can be called relative to an expected initial value, EIV, and an actual initial value, AIV, in addition to the target difference, δV. The endpoint logic can multiply the difference between the actual initial value and the expected initial value by a start value weight, SVW, in order to compensate for underlying variations from substrate to substrate. For example, the endpoint determination logic can end polishing when an endpoint metric, EM=SVW*(AIV−EIV)+δV.

In some implementations, a weighted combination is used to determine endpoint. For example, the endpoint determination logic can calculate an initial value of the characteristic from the function and a current value of the characteristic from the function, and a first difference between the initial value and the current value. The endpoint determination logic can calculate a second difference between the initial value and a target value and generate a weighted combination of the first difference and the second difference. Endpoint can be called with the weighted value reaches a target value. The endpoint determination logic can determine when an endpoint should be called by comparing the monitored difference (or differences) to a target difference of the characteristic. If the monitored difference matches or is beyond the target difference, an endpoint is called. In one implementation the monitored difference must match or exceed the target difference for some period of time (e.g., two revolutions of the platen) before an endpoint is called.

FIG. 9 shows a method 901 for choosing target values of characteristics associated with the selected spectral feature for a particular target thickness and particular endpoint determination logic. A set-up substrate is measured and polished as described above in steps 802-806 (step 903). In particular, spectra are collected and the time at which each collected spectrum is measured is stored.

A polishing rate of the polishing apparatus for the particular set-up substrate is calculated (step 905). The average polishing rate PR can be calculated by using the pre- and post-polished thicknesses Dl, D2, and the actual polish time, PT, e.g., PR=(D2−D1)/PT.

An endpoint time is calculated for the particular set-up substrate (step 907) to provide a calibration point to determine target values of the characteristics of the selected feature, as discussed below. The endpoint time can be calculated based on the calculated polish rate PR, the pre-polish starting thickness of the film of interest, ST, and the target thickness of the film of interest, TT. The endpoint time can be calculated as a simple linear interpolation, assuming that the polishing rate is constant through the polishing process, e.g., ET=(ST−TT)/PR.

Optionally, the calculated endpoint time can be evaluated by polishing another substrate of the batch of patterned substrates, stopping polishing at the calculated endpoint time, and measuring the thickness of the film of interest. If the thickness is within a satisfactory range of the target thickness, then the calculated endpoint time is satisfactory. Otherwise, the calculated endpoint time can be re-calculated.

Target characteristic values for the selected feature are recorded from the spectrum collected from the set-up substrate at the calculated endpoint time (step 909). If the parameters of interest involve a change in the selected feature's location or width, that information can be determined by examining the spectra collected during the period of time that preceded the calculated endpoint time. The difference between the initial values and the target values of the characteristics are recorded as the target differences for the feature. In some implementations, a single target difference is recorded.

FIG. 10 shows a method 1000 for using peak-based endpoint determination logic to determine an endpoint of a polishing step. Another substrate of the batch of patterned substrates is polished using the above-described polishing apparatus (step 1002).

An identification of a selected spectral feature, a wavelength range, and a characteristic of the selected spectral feature are received (step 1004). For example, the endpoint determination logic receives the identification from a computer with processing parameters for the substrate. In some implementations, the processing parameters are based on information determined during processing of a set-up substrate.

The substrate is initially polished, light reflecting from the substrate is measured to create a spectrum, and a characteristic value of the selected spectral feature is determined in the wavelength range of the measured spectrum. At each revolution of the platen, the following steps are performed.

One or more spectra of light reflecting off a substrate surface being polished are measured to obtain one or more current spectra for a current platen revolution (step 1006). The one or more spectra measured for the current platen revolution are optionally processed to enhance accuracy and/or precision as described above in reference to FIG. 8. If only one spectrum is measured, then the one spectrum is used as the current spectrum. If more than one current spectrum is measured for a platen revolution, then they are grouped, averaged within each group, and the averages are designated to be current spectra. The spectra can be grouped by radial distance from the center of the substrate.

By way of example, a first current spectrum can be obtained from spectra measured at points 202 and 210 (FIG. 2), a second current spectrum can be obtained from spectra measured at points 203 and 209, a third current spectra can be obtained from spectra measured at points 204 and 208, and so on. The characteristic values of the selected spectral peak can be determined for each current spectrum, and polishing can be monitored separately in each region of the substrate. Alternatively, worst-case values for the characteristics of the selected spectral peak can be determined from the current spectra and used by the endpoint determination logic.

During each revolution of the platen, an additional spectrum or spectra are added to the sequence of spectra for the current substrate. As polishing progresses at least some of the spectra in the sequence differ due to material being removed from the substrate during polishing.

Modified wavelength ranges for the current spectra are generated (step 1008) as described above with reference to FIGS. 7A-C. For example, the endpoint logic determines modified wavelength ranges for the current spectra based on previous characteristic values. The modified wavelength ranges can be centered on the previous characteristic values. In some implementations, the modified wavelength ranges are determined based on expected characteristic values, e.g., the center of the wavelength ranges coincide with the expected characteristic values.

In some implementations, some of the wavelength ranges for the current spectra are determined using different methods. For example, a wavelength range for a spectrum measured from light reflected in an edge area of the substrate is determined by centering the wavelength range on the characteristic value from the previous spectrum measured in the same edge area of the substrate. Continuing the example, a wavelength range for a spectrum measured from light reflected in a center area of the substrate is determined by centering the wavelength range on the expected characteristic value for the center area.

In some implementations, the widths of the wavelength ranges for the current spectra are the same. In some implementations, some of the widths of the wavelength ranges for the current spectra are different.

Identification of a wavelength range to search for selected spectral feature characteristics can allow greater accuracy in detection of endpoint or determination of a polishing rate change, e.g., the system is less likely to select an incorrect spectral feature during subsequent spectra measurements. Tracking spectral features in a wavelength range instead across an entire spectrum allows the spectral features to be more easily and quickly identified. Processing resources needed to identify the selected spectral features can be reduced

Current characteristic values for the selected peak are extracted from the modified wavelength ranges (step 1010), and the current characteristic values are compared to the target characteristic values (step 1012) using the endpoint determination logic discussed above in the context of FIG. 8. For example, a sequence of values for the current feature characteristic is determined from the sequence of spectra and a function is fit to the sequence of values. The function can be, for example, a non-linear function, e.g., a second order polynomial, that can approximate the amount of material removed from the substrate during polishing based on the difference between the current characteristic value and the initial characteristic value.

As long as the endpoint determination logic determines that the endpoint condition has not been met (“no” branch of step 1014), polishing is allowed to continue, and steps 1006, 1008, 1010, 1012, and 1014 are repeated as appropriate. For example, endpoint determination logic determines, based on the function, that the target difference for the feature characteristic has not yet been reached.

In some implementations, when spectra of reflected light from multiple portions of the substrate are measured, the endpoint determination logic can determine that the polishing rate of one or more portions of the substrate needs to be adjusted so that polishing of the multiple portions is completed at, or closer to the same time.

When the endpoint determination logic determines that the endpoint condition has been met (“yes” branch of step 1014), an endpoint is called, and polishing is stopped (step 1016).

Spectra can be normalized to remove or reduce the influence of undesired light reflections. Light reflections contributed by media other than the film or films of interest include light reflections from the polishing pad window and from the base silicon layer of the substrate. Contributions from the window can be estimated by measuring the spectrum of light received by the in-situ monitoring system under a dark condition (i.e., when no substrates are placed over the in-situ monitoring system). Contributions from the silicon layer can be estimated by measuring the spectrum of light reflecting of a bare silicon substrate. The contributions are usually obtained prior to commencement of the polishing step. A measured raw spectrum is normalized as follows:

normalized spectrum=(A−Dark)/(Si−Dark)

where A is the raw spectrum, Dark is the spectrum obtained under the dark condition, and Si is the spectrum obtained from the bare silicon substrate.

In the described embodiment, the change of a wavelength peak in the spectrum is used to perform endpoint detection. The change of a wavelength valley in the spectrum (that is, local minima) also can be used, either instead of the peak or in conjunction with the peak.

The change of multiple peaks (or valleys) also can be used when detecting the endpoint. For example, each peak can be monitored individually, and an endpoint can be called when a change of a majority of the peaks meet an endpoint condition. In other implementations, the change of an inflection point or an spectral zero-crossing can be used to determine endpoint detection.

In some implementations, an algorithm set-up process 1100 (FIG. 11) is followed by polishing of one or more substrate(s) using a triggered feature tracking technique 1200 (FIG. 12).

Initially, a characteristic of a feature of interest in a spectrum is selected for use in tracking polishing of a first layer (step 1102), e.g., using one of the techniques described above. For example, the feature can be a peak or valley, and the characteristic can be a position or width in wavelength or frequency of, or an intensity of, the peak or valley. If the characteristic of the feature of interest is applicable to a wide variety of product substrates of different patterns, then the feature and characteristic can be pre-selected by the equipment manufacturer.

In addition, the polishing rate dD/dt near the polishing endpoint is determined (step 1104). For example, a plurality of set-up substrates can be polished in accordance with the polishing process to be used for polishing of product substrates, but with different polishing times that are near the expected endpoint polishing time. The set-up substrates can have the same pattern as the product substrate. For each set-up substrate, the pre-polishing and post-polishing thickness of a layer can be measured, and the amount removed calculated from the difference, and the amount removed and the associated polishing time for that set-up substrate are stored to provide a data set. A linear function of amount removed as a function of time can be fit to the data set; the slope of the linear function provides the polishing rate. The algorithm set-up process includes measuring an initial thickness D₁ of a first layer of a set-up substrate (step 1106). The set-up substrate can have the same pattern as the product substrate. The first layer can be a dielectric, e.g., a low-k material, e.g., carbon doped silicon dioxide, e.g., Black Diamond™ (from Applied Materials, Inc.) or Coral™ (from Novellus Systems, Inc.).

Optionally, depending on the composition of the first material, one or more additional layers of another material, e.g., a dielectric material, different from both the first and second materials, e.g., a low-k capping material, e.g., tetraethyl orthosilicate (TEOS), is deposited over the first layer (step 1107). Together, the first layer and the one or more additional layers provide a layer stack.

Next, the second layer of a different second material, e.g., e.g., a barrier layer, e.g., a nitride, e.g., tantalum nitride or titanium nitride, is deposited over the first layer or layer stack (step 1108). In addition, a conductive layer, e.g., a metal layer, e.g., copper, can be deposited over the second layer (and in trenches provided by the pattern of the first layer) (step 1109).

Measurement can be performed at a metrology system other than the optical monitoring system to be used during polishing, e.g., an in-line or separate metrology station, such as a profilometer or optical metrology station that uses ellipsometry. For some metrology techniques, e.g., profilometry, the initial thickness of the first layer is measured before the second layer is deposited, but for other metrology techniques, e.g., ellipsometry, the measurement can be performed before or after the second layer is deposited. The set-up substrate is then polished in accordance with a polishing process of interest (step 1110). For example, the conductive layer and a portion of the second layer can be polished and removed at a first polishing station using a first polishing pad (step 1110 a). Then the second layer and a portion of the first layer can be polished and removed at a second polishing station using a second polishing pad (step 1110 b). However, it should be noted that for some implementations, the there is no conductive layer, e.g., the second layer is the outermost layer when polishing begins.

At least during the removal of second layer, and possibly during the entire polishing operation at the second polishing station, spectra are collected using techniques described above (step 1112). In addition, a separate detection technique is used to detect clearing of the second layer and exposure of the first layer (step 1114). For example, exposure of the first layer can be detected by a sudden change in the motor torque or total intensity of light reflected from the substrate. The value V₁ of the characteristic of the feature of interest of the spectrum at the time T₁ of clearing of the second layer is detected is stored. The time T₁ at which the clearing is detected can also be stored.

Polishing can be halted at a default time after detection of clearing (step 1118). The default time is sufficiently large that polishing is halted after exposure of the first layer. The default time is selected so that the post-polish thickness is sufficiently near the target thickness that the polishing rate can be assumed to be linear between the post-polishing thickness and the target thickness, or can be assumed to follow the non-linear function. The value V₂ of the characteristic of the feature of interest of the spectrum at the time polishing is halted can be detected and stored, as can the time T₂ at which polishing was halted.

The post-polish thickness D₂ of the first layer is measured, e.g., using the same metrology system as used to measure the initial thickness (step 1120).

A default target change in value ΔV_(D) of the characteristic is calculated (step 1122). This default target change in value will be used in the endpoint detection algorithm for the product substrate. The default target change can be calculated from the difference between the value at the time of clearing of the second layer and the value at the time polishing is halted, i.e., ΔV_(D)=V₁−V₂.

A rate of change of the thickness as a function of the monitored characteristic dD/dV near the end of the polishing operation is calculated (step 1124). For example, assuming that the wavelength position of a peak is being monitored, then the rate of change can be expressed as Angstroms of material removed per Angstroms of shift in wavelength position of the peak. As another example, assuming that the frequency width of a peak is being monitored, then the rate of change can be expressed as Angstroms of material removed per Hertz of shift in frequency of the width of the peak. In one implementation, a rate of change of the value as a function of time dV/dt can simply be calculated from the values at the times exposure of the second layer and at the end of polishing, e.g., dV/dt=(D₂ −D₁)/(T₂ −T₁). In another implementation, a non-linear function can be fit to the measured values as a function of time using data from near the end of the polishing of the set-up substrate, e.g., the last 25% or less of the time between T₁ and T₂; the local slope of the non-linear function provides a rate of change of the value as a function of time dV/dt. In either case, the rate of change of the thickness as a function of the monitored characteristic dD/dV is then calculated by dividing the polishing rate by the rate of change of the value, i.e., dD/dV=(dD/dt)/(dV/dt). Once the rate of change dD/dV is calculated it should be remain constant for a product; it should not be necessary to recalculate dD/dV for different lots of the same product.

Once the set-up process has been completed, product substrates can be polished.

Optionally, an initial thickness d₁ of a first layer of at least one substrate from a lot of product substrate is measured (step 1202). The product substrates have at least the same layer structure, and optionally the same pattern, as the set-up substrates. In some implementations, not every product substrate is measured. For example, one substrate from a lot can be measured, and the initial thickness used for all other substrates from the lot. As another example, one substrate from a cassette can be measured, and the initial thickness used for all other substrates from the cassette. In other implementations, every product substrate is measured. Measurement of the thickness of the first layer of the product substrate can be performed before or after the set-up process is complete.

As noted above, the first layer can be a dielectric, e.g., a low-k material, e.g., carbon doped silicon dioxide, e.g., Black Diamond™ (from Applied Materials, Inc.) or Coral™ (from Novellus Systems, Inc.). Measurement can be performed at a metrology system other than the optical monitoring system to be used during polishing, e.g., an in-line or separate metrology station, such as a profilometer or optical metrology station that uses ellipsometry. Optionally, depending on the composition of the first material, one or more additional layers of another material, different from both the first and second materials, e.g., a low-k capping material, e.g., tetraethyl orthosilicate (TEOS), is deposited over the first layer on the product substrate (step 1203). Together, the first layer and the one or more additional layers provide a layer stack.

Next, the second layer of a different second material, e.g., e.g., a barrier layer, e.g., a nitride, e.g., tantalum nitride or titanium nitride, is deposited over the first layer or layer stack of the product substrate (step 1204). In addition, a conductive layer, e.g., a metal layer, e.g., copper, can be deposited over the second layer of the product substrate (and in trenches provided by the pattern of the first layer) (step 1205). However, it should be noted that for some implementations, there is no conductive layer, e.g., the second layer is the outermost layer when polishing begins.

For some metrology techniques, e.g., profilometry, the initial thickness of the first layer is measured before the second layer is deposited, but for other metrology techiques, e.g., ellipsometry, the measurement can be performed before or after the second layer is deposited. Deposition of the second layer and the conductive layer can be performed before or after the set-up process is complete.

For each product substrate to be polished, a target characteristic difference ΔV is calculated based on the initial thickness of the first layer (step 1206). Typically, this occurs before polishing begins, but it is possible for the calculation to occur after polishing begins but before the spectra feature tracking is initiated (in step 1210). In particular, the stored initial thickness d₁ of the product substrate is received, e.g., from a host computer, along with a target thickness d_(T). In addition, the starting and ending thicknesses D₁ and D₂, the rate of change of the thickness as a function of the monitored characteristic dD/dV, and the default target change in value ΔV_(D) determined for the set-up substrate can be received.

In one implementation, the target characteristic difference ΔV is calculated as follows:

ΔV=ΔV_(D)+(d ₁ −D ₁)/(dD/dV)+(D₂−d_(T))/(dD/dV)

In some implementations, the pre-thickness will not be available. In this case, the “(d₁−D₁)/(dD/dV)” will be omitted from the above equation, i.e.,

ΔV=ΔV _(D)+(D ₂ −d _(T))/(dD/dV)

The product substrate is polished (step 1208). For example, the conductive layer and a portion of the second layer can be polished and removed at a first polishing station using a first polishing pad (step 1208 a). Then the second layer and a portion of the first layer can be polished and removed at a second polishing station using a second polishing pad (step 1208 b). However, it should be noted that for some implementations, the there is no conductive layer, e.g., the second layer is the outermost layer when polishing begins.

An in-situ monitoring technique is used to detect clearing of the second layer and exposure of the first layer (step 1210). For example, exposure of the first layer at a time t1 can be detected by a sudden change in the motor torque or total intensity of light reflected from the substrate. For example, FIG. 13 shows a graph of the total intensity of light received from the substrate as a function of time during polishing of a metal layer to expose an underlying barrier layer. This total intensity can be generated from the spectral signal acquired by the spectral monitoring system by integrating the spectral intensity, e.g., across the all of wavelengths measured or across a preset wavelength range. Alternatively, rather than a total intensity, the intensity at a specific monochromatic wavelength can be used. As shown by FIG. 13, as the copper layer is being cleared, the total intensity falls, and when the barrier layer is completely exposed, the total intensity levels off. The leveling off of the intensity can be detected and used as a trigger to initiate the spectral feature tracking

Beginning at least with detection of the clearance of second layer (and potentially earlier, e.g., from the beginning of polishing of the product substrate with the second polishing pad), spectra are obtained during polishing using the in-situ monitoring techniques described above (step 1212). The spectra are analyzed using the techniques described above to determine the value of the characteristic of the feature being tracked. For example, FIG. 14 illustrates a graph of the wavelength position of a spectral peak as a function of time during polishing. The value v₁ of the characteristic of the feature being tracked in the spectrum at the time t₁ of clearing of the second layer is detected is determined.

The target value v_(T) for the characteristic can now be calculated (step 1214). The target value v_(T) can be calculated by adding the target characteristic difference ΔV to the value v₁ of the characteristic at the time t₁ of clearing of the second layer, i.e., v_(T)=v₁+ΔV.

When the characteristic of the feature being tracked reaches the target value, polishing is halted (step 1216). In particular, for each measured spectrum, e.g., in each platen rotation, the value of the characteristic of the feature being tracked is determined to generate a sequence of values. As described above with reference to FIG. 6A, a function, e.g., a non-linear function of time, can be fit to the sequence of values. In some implementations, the function can be fit to values within a time window. Where the function meets the target value provides the endpoint time at which polishing is halted. The value v₁ of the characteristic at the time t₁ of clearing of the second layer is detected can also be determined by fitting a function, e.g., a non-linear function, to portion of the sequence of values near time t₁.

Although the method illustrated by FIGS. 12 and 13 includes deposition and removal of a second layer, for some implementations, there is no second layer, e.g., the first layer is the outermost layer when polishing begins. For example, the process of measuring an initial thickness of the first layer prior to polishing and calculating a target feature value from the initial thickness and the target thickness can be applicable with or without an overlying second layer; the second layer is optional. In particular, the step of depositing the second layer, and the step of detecting the exposure of the first layer, can be omitted. Such a first layer can include polysilicon and/or dielectric material, e.g., consist of substantially pure polysilicon, consist of dielectric material, or be a combination of polysilicon and dielectric material. The dielectric material can be an oxide, e.g., silicon oxide, or a nitride, e.g., silicon nitride, or a combination of dielectric materials.

For example, an initial thickness d₁ of the first layer of at least one substrate from a lot of product substrates is measured (e.g., as discussed for step 1202). A target characteristic difference AV is calculated based on the initial thickness of the first layer (e.g., as discussed for step 1206). Polishing of the first layer of the product substrate is initiated, and spectra are obtained during polishing of the first layer using the in-situ monitoring techniques described above. The value v₁ of the characteristic can be measured during polishing of the first layer, e.g., immediately upon or soon after, e.g., a few seconds after, initiating polishing of the first layer. Waiting a few seconds can permit signals from the monitoring system to stabilize so that the measurement of the value v₁ is more accurate. A target value v_(T) for the characteristic can be calculated (e.g., as discussed for step 1214). For example, the target characteristic difference ΔV can be added to the value v₁ of the characteristic, i.e., v_(T)=v₁+ΔV. When the characteristic of the feature being tracked reaches the target value, polishing is halted (e.g., as discussed for step 1216). This approach permits removal to a target thickness, while compensating for variations from substrate to substrate in the absolute peak location due to substrate-to-substrate differences in underlying structure.

There are many techniques to remove noise from the sequence of values. Although fitting a line to the sequence is discussed above, a non-linear function could be fit to the sequence, or a low pass median filter could be used to smooth the sequence (in which case the filtered value could be directly compared to the target value to determine the endpoint).

Although the description above focuses on tracking a characteristic of a spectral feature, e.g., a wavelength or width of a peak or valley, as noted above, a non-linear function can be fit to a sequence of values from other in-situ monitoring techniques, e.g., for a sequence of thickness values obtained by matching reference spectra, or for a sequence of values generated by an eddy current monitoring system (e.g., during monitoring of polishing of a metal layer).

As used in the instant specification, the term substrate can include, for example, a product substrate (e.g., which includes multiple memory or processor dies), a test substrate, a bare substrate, and a gating substrate. The substrate can be at various stages of integrated circuit fabrication, e.g., the substrate can be a bare wafer, or it can include one or more deposited and/or patterned layers. The term substrate can include circular disks and rectangular sheets.

Embodiments of the invention and all of the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structural means disclosed in this specification and structural equivalents thereof, or in combinations of them. Embodiments of the invention can be implemented as one or more computer program products, i.e., one or more computer programs tangibly embodied in an information carrier, e.g., in a machine-readable storage device or in a propagated signal, for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor, a computer, or multiple processors or computers. A computer program (also known as a program, software, software application, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file. A program can be stored in a portion of a file that holds other programs or data, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.

The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

The above described polishing apparatus and methods can be applied in a variety of polishing systems. Either the polishing pad, or the carrier head, or both can move to provide relative motion between the polishing surface and the substrate. For example, the platen may orbit rather than rotate. The polishing pad can be a circular (or some other shape) pad secured to the platen. Some aspects of the endpoint detection system may be applicable to linear polishing systems, e.g., where the polishing pad is a continuous or a reel-to-reel belt that moves linearly. The polishing layer can be a standard (for example, polyurethane with or without fillers) polishing material, a soft material, or a fixed-abrasive material. Terms of relative positioning are used; it should be understood that the polishing surface and substrate can be held in a vertical orientation or some other orientation.

Particular embodiments have been described. Other embodiments are within the scope of the following claims. For example, the actions recited in the claims can be performed in a different order and still achieve desirable results. 

1. A method of controlling polishing, comprising: polishing a substrate; monitoring a substrate during polishing with an in-situ monitoring system; generating a sequence of values from measurements from the in-situ monitoring system; fitting a non-linear function to the sequence of values; determining a projected time at which the non-linear function reaches a target value; and determining at least one of a polishing endpoint or an adjustment for a polishing rate based on the projected time.
 2. The method of claim 1, wherein the non-linear function comprises a second order or higher polynomial function.
 3. The method of claim 2, wherein the non-linear function consists of a second order polynomial function.
 4. The method of claim 1, wherein fitting the non-linear function to the sequence of values comprises a Savitzky-Golay method.
 5. The method of claim 1, wherein the in-situ monitoring system comprises a spectrographic monitoring system and further comprising measuring a sequence of spectra of light from the substrate during polishing with the spectrographic monitoring system.
 6. The method of claim 5, further comprising: for each measured spectrum from the sequence of spectra, finding a best matching reference spectrum from a library having a plurality of reference spectra; and wherein generating the sequence of values includes, for each best matching reference spectrum, determining a value associated the best matching reference spectrum.
 7. The method of claim 6, wherein the sequence of values comprises a sequence of thicknesses values.
 8. The method of claim 5, further comprising: for each measured spectrum from the sequence of spectra, finding a position or width of a peak or valley of the measured spectrum to generate a sequence of position or width values; and wherein the sequence of values is generated from the sequence of position or width values.
 9. The method of claim 8, wherein the sequence of values comprises a sequence of wavelength values of positions of the peak or valley.
 10. The method of claim 5, wherein polishing the substrate comprises polishing a dielectric and/or semiconductor layer.
 11. The method of claim 1, wherein the in-situ monitoring system comprises an eddy current monitoring system, and further comprising generating the sequence of values with the eddy current monitoring system.
 12. The method of claim 11, wherein polishing the substrate comprises polishing a metal layer.
 13. The method of claim 1, further comprising halting the polishing when the non-linear function matches or exceeds a target value.
 14. The method of claim 1, wherein the substrate includes a plurality of zones, and a polishing rate of each zone is independently controllable by an independently variable polishing parameter, and further comprising: for each zone, generating a sequence of values from measurements from the in-situ monitoring system during polishing; based on the sequence of values for each zone, adjusting the polishing parameter for at least one zone to adjust the polishing rate of the at least one zone such that the plurality of zones have a smaller difference in thickness at the polishing endpoint than without such adjustment.
 15. The method of claim 1, wherein the substrate includes a plurality of zones, and a polishing rate of each zone is independently controllable by an independently variable polishing parameter, and further comprising: measuring a sequence of spectra from each zone during polishing; for each zone, generating a sequence of values, including for each measured spectrum of the sequence of spectra, determining a wavelength or width of a peak or valley of a spectral feature; and based on the sequence of values for each zone, adjusting the polishing parameter for at least one zone to adjust the polishing rate of the at least one zone such that the plurality of zones have a smaller difference in thickness at the polishing endpoint than without such adjustment.
 16. The method of claim 1, wherein polishing the substrate comprises polishing a layer that includes polysilicon and/or a dielectric material, and monitoring the substrate comprises monitoring the layer.
 17. The method of claim 16, wherein the layer consists of substantially pure polysilicon.
 18. The method of claim 16, wherein the layer consists of dielectric material.
 19. The method of claim 16, wherein the layer is a combination of polysilicon and dielectric material.
 20. A method of controlling polishing, comprising: polishing a substrate; measuring a sequence of spectra of light from the substrate during polishing; generating a sequence of values, including for each measured spectrum of the sequence of spectra, determining a wavelength or width of a peak or valley of a spectra feature; fitting a non-linear function to the sequence of values; determining a projected time at which the non-linear function reaches a target value; and determining at least one of a polishing endpoint or an adjustment for a polishing rate based on the projected time. 